In order to achieve long-term covert precise navigation for an underwater vehicle, the shortcomings of various underwater navigation methods used are analyzed. Given the low navigation precision of underwater mapmatching aided inertial navigation based on singlegeophysical information, a model of an underwater mapmatching aided inertial navigation system based on multigeophysical information (gravity, topography and geomagnetism) is put forward, and the key technologies of map-matching based on multi-geophysical information are analyzed. Iterative closest contour point (ICCP) mapmatching algorithm and data fusion based on DempsterShafer (D-S) evidence theory are applied to navigation simulation. Simulation results show that accumulation of errors with increasing of time and distance are restrained and fusion of multi-map-matching is superior to any single-map-matching, which can effectively determine the best match of underwater vehicle position and improve the accuracy of underwater vehicle navigation.

Non-line-of-sight (NLOS) propagation biases Time of Arrival (TOA) and Time Difference of Arrival (TDOA). It causes the principal error for the mobile location in cellular networks.To mitigate the positioning error, a mobile positioning approach based on modified Kalman filter is proposed in this paper. With this approach, the true range is estimated based on the measurements, and the estimated range is utilized to location solution, which can reduce the impact of NLOS effectively. In our approach, the modified Kalman filter adapt it's parameters with the estimate of NLOS's standard deviation, which make the approach remain effective in different environments. Simulation results show that this approach presents a good positioning accuracy even under NLOS propagation environments. The approach can be well applicable to mobile location in cellular networks.

In TDOA cellular mobile location, Non-Line-of-Sight (NLOS) propagation of radio waves brings about the larger errors of TOA/TDOA parameter measurements, thus resulting in location accuracy decreasing seriously. On the basis of TDOA errors analysis and NLOS characteristics investigation, a NLOS mitigation algorithm is proposed in this paper to realize the TDOA smoothing and LOS reconstruction by Kalman filter in NLOS propagation environment, which effectively inhibits NLOS error of mobile location, so that positioning errors are reduced greatly. Simulation results show that the proposed algorithm can significantly improve the positioning accuracy and performance of TDOA mobile location under NLOS conditions. Combining with the WLS location resolving algorithm, the proposed algorithm can be well applied to mobile location of CDMA2000 cellular networks.

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